00985986

Component

https://doi.org/10.3141/1886-04

http://scholar.google.com...abib&publication_year=2004

Vehicle reidentification is the process of tracking a vehicle along a highway as it crosses detection stations. Inductive loop detectors are by far the most widely deployed vehicle detectors. In the present work, vehicle reidentification is performed by combining vehicle-specific information (length and electromagnetic signatures) and some contextual information (lane, speed, and time) to form a decision tree. This approach provides a specific decision tree for tracking vehicles along each highway section. After training, the decision tree successfully classified about 95% of the unseen test records--a significant improvement relative to the literature and our own previous work on the same data. This success rate has been consistently obtained from two data sets: one consisting only of passenger vehicles and another consisting of a representative traffic mix.

This paper appears in Transportation Research Record No. 1886, Intelligent Transportation Systems and Vehicle-Highway Automation 2004.

00985982

English

p. 24-33

2004

Transportation Research Record

030909481X

Figures (7) ; References (15) ; Tables (2)

Accuracy; Decision trees; Detection and identification systems

Electromagnetic signatures; Vehicle reidentification

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning; I73: Traffic Control

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